Coloring Book

Generator

Unpaired style

transfer using

CycleGAN

-Aanchal Sahu

-Venkatakrishnan

Ranganathan

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Why should you care as adults?

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●Offline stress reduction alternative

●Shortcut

●Encourages artistic expression and

motor skills

●Can call it a hobby

●Sense of achievement

FiftyOne

•FiftyOne provides

powerful tools for

visualizing and

exploring data.

•The combined power of

CLIP and FiftyOne

allows for accurate and

efficient image

similarity search and

retrieval.

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CycleGAN

Unpaired

Image to

Image style

transfer

Capturing

common

characteris

tics of a

set of

images

Applying

that to

another set

of images.

Two

Generators

and two

discriminat

ors

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Design

•Least Squares Generative Adversarial Networks

(LSGANs)

+Improved Image Quality

+Enhanced Stability in Learning

•Domain X: Real World images of Objects, animals,

people and scenery

•Domain Y: Sketches and coloring book images (Black

and white)

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Dataset Domain X

Open Images Dataset

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Dataset Domain Y

Imagenet-Sketch Drawings from Museums

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Experiments

•Images get sharper with

more data

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Results

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Results

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Evaluation: PSNR (Peak Signal-to-Noise Ratio)

•Distortion, noise, information loss, and pixel intensity.

•Higher PSNR = better image similarity and quality. Anything

between 30-50 dB is considered good.

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Analysis: PSNR

•The CLIP version

performs better in

the PSNR

evaluation metric.

•Our scores always

lie between 27.01-

31.57 dB since the

original image and

coloring book

version look quite

different.

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Evaluation: SSIM (Structural Similarity Index)

●Structural information, luminance, contrast, and

similarity of patterns in the images.

●Higher SSIM values = greater similarity and

better quality. Ranges from 0 to 1, with 1

representing a perfect match.

●SSIM is more aligned with human perception than

PSNR and considers factors like brightness and

texture.

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Analysis: SSIM

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●Wide range.

●Some images

are very

similar to the

original image

while some are

very

different.

●The third

attempt seems

to perform the

best for this

evaluation

metric.

Problems and Future Work

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